test: add unit tests for tool calling test runner (#101)

- Update raw-IP forge URL to canonical forge domain in README.md
  (fixes #46)
- Update 4 broken local markdown links pointing to deleted
  BUILD-SPEC.md, PHASE1-REPORT.md, FULL-REPORT.md to
  docs/PROJECT_STATUS.md (fixes #44)

.gitignore

@@ -0,0 +1,3 @@
+build/
+*.pyc
+__pycache__/

CMakeLists.txt

@@ -0,0 +1,36 @@
+cmake_minimum_required(VERSION 3.16)
+
+project(turboquant LANGUAGES CXX)
+
+option(TURBOQUANT_BUILD_TESTS "Build standalone TurboQuant validation tests" ON)
+
+add_library(turboquant STATIC
+    llama-turbo.cpp
+)
+
+target_include_directories(turboquant PUBLIC
+    ${CMAKE_CURRENT_SOURCE_DIR}
+)
+
+target_compile_features(turboquant PUBLIC cxx_std_17)
+
+if(MSVC)
+    target_compile_options(turboquant PRIVATE /W4)
+else()
+    target_compile_options(turboquant PRIVATE -Wall -Wextra -Wpedantic)
+endif()
+
+if(TURBOQUANT_BUILD_TESTS)
+    include(CTest)
+
+    add_executable(turboquant_roundtrip_test
+        tests/roundtrip_test.cpp
+    )
+    target_link_libraries(turboquant_roundtrip_test PRIVATE turboquant)
+    target_compile_features(turboquant_roundtrip_test PRIVATE cxx_std_17)
+
+    add_test(
+        NAME turboquant_roundtrip
+        COMMAND turboquant_roundtrip_test
+    )
+endif()

README.md

@@ -13,7 +13,7 @@ Unlock 64K-128K context on qwen3.5:27b within 32GB unified memory.
 A 27B model at 128K context with TurboQuant beats a 72B at Q2 with 8K context.
 
 ## Status
-See [issues](http://143.198.27.163:3000/Timmy_Foundation/turboquant/issues) for current progress.
+See [issues](https://forge.alexanderwhitestone.com/Timmy_Foundation/turboquant/issues) for current progress.
 
 ## Roles
 - **Strago:** Build spec author
@@ -29,4 +29,4 @@ See [issues](http://143.198.27.163:3000/Timmy_Foundation/turboquant/issues) for
 - [rachittshah/mlx-turboquant](https://github.com/rachittshah/mlx-turboquant) — MLX fallback
 
 ## Docs
-- [BUILD-SPEC.md](BUILD-SPEC.md) — Full build specification (Strago, v2.2)
+- [Project Status](docs/PROJECT_STATUS.md) — Full project status and build specification

benchmarks/bonsai-tool-calling.md

@@ -0,0 +1,50 @@
+# Tool Calling Viability: Bonsai 1-Bit Models
+
+**Epic**: #99 (1-Bit Models + Edge)
+**Date**: TBD (run benchmarks/test_tool_calling.py to populate)
+
+## Hypothesis
+
+1-bit quantization destroys fine-grained reasoning. Tool calling (precise JSON output) may be impossible at Q1_0. But worth testing — the field is moving fast.
+
+## Models to Test
+
+| Model | Size | Quant | Source |
+|-------|------|-------|--------|
+| Bonsai-1.7B | 1.7B | Q1_0 | prism-ml/Bonsai-1.7B-gguf |
+| Bonsai-4B | 4B | Q1_0 | prism-ml/Bonsai-4B-gguf |
+| Bonsai-8B | 8B | Q1_0 | prism-ml/Bonsai-8B-gguf |
+
+## Test Suite
+
+| # | Test | Category | Description |
+|---|------|----------|-------------|
+| 1 | simple_file_read | Simple Tool Call | Read a file with an exact path |
+| 2 | terminal_command | Terminal Command | Execute a shell command |
+| 3 | web_search | Web Search | Search the web for a query |
+| 4 | multi_step_chain | Multi-Step | Chain: read -> analyze -> write |
+| 5 | nested_schema | Schema Parsing | Complex nested parameters |
+
+## Results
+
+> **Run**: `python3 benchmarks/test_tool_calling.py --model bonsai-1.7b --output benchmarks/bonsai-tool-calling.md`
+
+| Test | Bonsai-1.7B | Bonsai-4B | Bonsai-8B |
+|------|-------------|-----------|-----------|
+| simple_file_read | TBD | TBD | TBD |
+| terminal_command | TBD | TBD | TBD |
+| web_search | TBD | TBD | TBD |
+| multi_step_chain | TBD | TBD | TBD |
+| nested_schema | TBD | TBD | TBD |
+
+## Verdict
+
+TBD — run the test suite to populate.
+
+## Failure Modes (if any)
+
+TBD — document specific failure patterns observed.
+
+## Recommendations
+
+TBD — based on results, recommend minimum viable quantization level for tool calling.

benchmarks/test_tool_calling.py

@@ -0,0 +1,435 @@
+#!/usr/bin/env python3
+"""
+Tool Calling Viability Test for 1-Bit / Edge Models (Issue #101)
+
+Tests whether Bonsai 1-bit models (or any small model) can produce
+valid tool calls via Ollama or llama-server API.
+
+Test suite (5 categories):
+  1. Simple tool call: file read with exact path
+  2. Terminal command execution
+  3. Web search
+  4. Multi-step: read file -> analyze -> write result
+  5. Schema parsing: complex nested parameters
+
+Each test:
+  - Sends a prompt requesting a tool call
+  - Checks if the response contains valid JSON tool call syntax
+  - Scores structural validity + semantic accuracy
+  - Records latency and token count
+
+Usage:
+    python3 benchmarks/test_tool_calling.py --model bonsai-1.7b
+    python3 benchmarks/test_tool_calling.py --model qwen3.5 --backend llama-server --url http://localhost:8080
+    python3 benchmarks/test_tool_calling.py --model bonsai-1.7b --output benchmarks/bonsai-tool-calling.md
+"""
+
+import argparse
+import json
+import os
+import re
+import sys
+import time
+from datetime import datetime, timezone
+from typing import Optional
+
+try:
+    import requests
+except ImportError:
+    print("Error: pip install requests", file=sys.stderr)
+    sys.exit(1)
+
+
+# ── Tool call test definitions ────────────────────────────────────────
+
+TESTS = [
+    {
+        "id": "simple_file_read",
+        "category": "Simple Tool Call",
+        "description": "Read a file with an exact path",
+        "prompt": (
+            "You have access to a tool called read_file. "
+            "Call it to read /etc/hostname. "
+            "Respond ONLY with a JSON tool call in this exact format:\n"
+            '{"name": "read_file", "arguments": {"path": "/etc/hostname"}}'
+        ),
+        "validate": lambda resp: _has_json_tool_call(resp, "read_file", {"path": "/etc/hostname"}),
+        "scoring": "structural",  # Can we parse the JSON at all?
+    },
+    {
+        "id": "terminal_command",
+        "category": "Terminal Command",
+        "description": "Execute a shell command",
+        "prompt": (
+            "You have access to a tool called terminal. "
+            "Call it to run the command: echo hello world. "
+            "Respond ONLY with a JSON tool call:\n"
+            '{"name": "terminal", "arguments": {"command": "echo hello world"}}'
+        ),
+        "validate": lambda resp: _has_json_tool_call(resp, "terminal", {"command": "echo hello world"}),
+        "scoring": "structural",
+    },
+    {
+        "id": "web_search",
+        "category": "Web Search",
+        "description": "Search the web for a query",
+        "prompt": (
+            "You have access to a tool called web_search. "
+            "Search for: what is quantization in machine learning. "
+            "Respond ONLY with a JSON tool call:\n"
+            '{"name": "web_search", "arguments": {"query": "what is quantization in machine learning"}}'
+        ),
+        "validate": lambda resp: _has_json_tool_call(resp, "web_search", {"query": "what is quantization in machine learning"}),
+        "scoring": "structural",
+    },
+    {
+        "id": "multi_step_chain",
+        "category": "Multi-Step",
+        "description": "Chain: read file -> analyze -> write result",
+        "prompt": (
+            "You have access to these tools: read_file, write_file.\n"
+            "Task: Read /tmp/input.txt, count the words, then write the count to /tmp/count.txt.\n"
+            "First, call read_file on /tmp/input.txt. "
+            "Respond ONLY with the first tool call as JSON:\n"
+            '{"name": "read_file", "arguments": {"path": "/tmp/input.txt"}}'
+        ),
+        "validate": lambda resp: _has_json_tool_call(resp, "read_file", {"path": "/tmp/input.txt"}),
+        "scoring": "structural",
+    },
+    {
+        "id": "nested_schema",
+        "category": "Schema Parsing",
+        "description": "Complex nested parameters",
+        "prompt": (
+            "You have access to a tool called deploy_service. "
+            "Deploy a service with:\n"
+            '- name: "api-gateway"\n'
+            '- replicas: 3\n'
+            '- env: {"PORT": 8080, "NODE_ENV": "production"}\n'
+            '- resources: {"cpu": "500m", "memory": "256Mi"}\n\n'
+            "Respond ONLY with a JSON tool call:\n"
+            '{"name": "deploy_service", "arguments": {"name": "api-gateway", "replicas": 3, '
+            '"env": {"PORT": 8080, "NODE_ENV": "production"}, '
+            '"resources": {"cpu": "500m", "memory": "256Mi"}}}'
+        ),
+        "validate": lambda resp: _has_nested_tool_call(resp),
+        "scoring": "semantic",  # Needs correct nested structure
+    },
+]
+
+
+# ── Validation helpers ────────────────────────────────────────────────
+
+def _extract_json(text: str) -> Optional[dict]:
+    """Try to extract a JSON object from text."""
+    # Try direct parse
+    text = text.strip()
+    try:
+        obj = json.loads(text)
+        if isinstance(obj, dict):
+            return obj
+    except json.JSONDecodeError:
+        pass
+
+    # Try finding JSON in code blocks
+    code_block = re.search(r"```(?:json)?\s*({.*?})\s*```", text, re.DOTALL)
+    if code_block:
+        try:
+            return json.loads(code_block.group(1))
+        except json.JSONDecodeError:
+            pass
+
+    # Try finding any JSON object
+    json_match = re.search(r"({[^{}]*(?:{[^{}]*}[^{}]*)*})", text)
+    if json_match:
+        try:
+            return json.loads(json_match.group(1))
+        except json.JSONDecodeError:
+            pass
+
+    return None
+
+
+def _has_json_tool_call(resp: str, expected_name: str, expected_args: dict) -> dict:
+    """Check if response contains a valid tool call with expected name and args."""
+    obj = _extract_json(resp)
+    if obj is None:
+        return {"passed": False, "reason": "no JSON found in response"}
+
+    # Check name
+    name = obj.get("name", obj.get("function", {}).get("name", ""))
+    if name != expected_name:
+        return {"passed": False, "reason": f"wrong tool name: {name!r}, expected {expected_name!r}"}
+
+    # Check arguments exist
+    args = obj.get("arguments", obj.get("function", {}).get("arguments", obj.get("args", {})))
+    if not args:
+        return {"passed": False, "reason": "no arguments found"}
+
+    # Check key arguments match
+    for key, val in expected_args.items():
+        if key not in args:
+            return {"passed": False, "reason": f"missing argument: {key}"}
+        if args[key] != val:
+            return {"passed": False, "reason": f"argument mismatch: {key}={args[key]!r}, expected {val!r}"}
+
+    return {"passed": True, "reason": "tool call valid", "parsed": obj}
+
+
+def _has_nested_tool_call(resp: str) -> dict:
+    """Check if response contains a valid tool call with nested parameters."""
+    obj = _extract_json(resp)
+    if obj is None:
+        return {"passed": False, "reason": "no JSON found in response"}
+
+    name = obj.get("name", obj.get("function", {}).get("name", ""))
+    if name != "deploy_service":
+        return {"passed": False, "reason": f"wrong tool name: {name!r}"}
+
+    args = obj.get("arguments", obj.get("function", {}).get("arguments", obj.get("args", {})))
+    if not args:
+        return {"passed": False, "reason": "no arguments found"}
+
+    checks = {
+        "name": str,
+        "replicas": int,
+        "env": dict,
+        "resources": dict,
+    }
+
+    for key, expected_type in checks.items():
+        if key not in args:
+            return {"passed": False, "reason": f"missing nested key: {key}"}
+        if not isinstance(args[key], expected_type):
+            return {"passed": False, "reason": f"{key} should be {expected_type.__name__}, got {type(args[key]).__name__}"}
+
+    # Check env has PORT
+    env = args.get("env", {})
+    if "PORT" not in env:
+        return {"passed": False, "reason": "env missing PORT"}
+
+    return {"passed": True, "reason": "nested tool call valid", "parsed": obj}
+
+
+# ── Backend runners ───────────────────────────────────────────────────
+
+def run_ollama(prompt: str, model: str, url: str, timeout: int = 120) -> dict:
+    """Run a prompt against Ollama."""
+    api_url = f"{url.rstrip('/')}/api/generate"
+    start = time.time()
+    try:
+        resp = requests.post(api_url, json={
+            "model": model,
+            "prompt": prompt,
+            "stream": False,
+            "options": {"num_predict": 256, "temperature": 0}
+        }, timeout=timeout)
+        elapsed = time.time() - start
+        resp.raise_for_status()
+        data = resp.json()
+        return {
+            "response": data.get("response", ""),
+            "latency_s": round(elapsed, 3),
+            "tokens": data.get("eval_count", 0),
+            "status": "success",
+        }
+    except Exception as e:
+        return {"response": "", "latency_s": round(time.time() - start, 3), "tokens": 0, "status": "failed", "error": str(e)}
+
+
+def run_llama_server(prompt: str, model: str, url: str, timeout: int = 120) -> dict:
+    """Run a prompt against llama-server (OpenAI-compatible)."""
+    api_url = f"{url.rstrip('/')}/v1/chat/completions"
+    start = time.time()
+    try:
+        resp = requests.post(api_url, json={
+            "model": model,
+            "messages": [
+                {"role": "system", "content": "You are a tool-calling assistant. Respond ONLY with JSON tool calls."},
+                {"role": "user", "content": prompt},
+            ],
+            "max_tokens": 256,
+            "temperature": 0,
+            "stream": False,
+        }, timeout=timeout)
+        elapsed = time.time() - start
+        resp.raise_for_status()
+        data = resp.json()
+        content = data.get("choices", [{}])[0].get("message", {}).get("content", "")
+        usage = data.get("usage", {})
+        return {
+            "response": content,
+            "latency_s": round(elapsed, 3),
+            "tokens": usage.get("completion_tokens", 0),
+            "status": "success",
+        }
+    except Exception as e:
+        return {"response": "", "latency_s": round(time.time() - start, 3), "tokens": 0, "status": "failed", "error": str(e)}
+
+
+# ── Main runner ───────────────────────────────────────────────────────
+
+def run_tests(model: str, backend: str = "ollama", url: str = "http://localhost:11434",
+              timeout: int = 120, verbose: bool = False) -> dict:
+    """Run the full tool calling test suite."""
+    runner_fn = run_ollama if backend == "ollama" else run_llama_server
+
+    results = {
+        "model": model,
+        "backend": backend,
+        "url": url,
+        "timestamp": datetime.now(timezone.utc).isoformat(),
+        "tests": [],
+        "summary": {"total": 0, "passed": 0, "failed": 0, "errors": 0},
+    }
+
+    print(f"Testing tool calling on: {model} ({backend})\n")
+
+    for test in TESTS:
+        print(f"  [{test['id']}] {test['description']}...", end=" ", flush=True)
+
+        run_result = runner_fn(test["prompt"], model, url, timeout)
+
+        if run_result["status"] == "failed":
+            result = {
+                "id": test["id"],
+                "category": test["category"],
+                "description": test["description"],
+                "passed": False,
+                "reason": f"backend error: {run_result.get('error', 'unknown')}",
+                "response": "",
+                "latency_s": run_result["latency_s"],
+                "tokens": 0,
+            }
+            results["summary"]["errors"] += 1
+            print("ERROR")
+        else:
+            validation = test["validate"](run_result["response"])
+            result = {
+                "id": test["id"],
+                "category": test["category"],
+                "description": test["description"],
+                "passed": validation["passed"],
+                "reason": validation["reason"],
+                "response": run_result["response"][:500],
+                "latency_s": run_result["latency_s"],
+                "tokens": run_result["tokens"],
+            }
+            if validation["passed"]:
+                results["summary"]["passed"] += 1
+                print("PASS")
+            else:
+                results["summary"]["failed"] += 1
+                print(f"FAIL ({validation['reason']})")
+
+        if verbose:
+            print(f"    Response: {run_result['response'][:200]}")
+
+        results["summary"]["total"] += 1
+        results["tests"].append(result)
+
+    return results
+
+
+def to_markdown(results: dict) -> str:
+    """Format test results as a markdown report."""
+    lines = []
+    lines.append(f"# Tool Calling Viability: {results['model']}")
+    lines.append("")
+    lines.append(f"**Date**: {results['timestamp']}")
+    lines.append(f"**Backend**: {results['backend']} ({results['url']})")
+    lines.append(f"**Model**: {results['model']}")
+    lines.append("")
+
+    s = results["summary"]
+    pass_rate = s["passed"] / s["total"] * 100 if s["total"] > 0 else 0
+    lines.append(f"## Summary: {s['passed']}/{s['total']} passed ({pass_rate:.0f}%)")
+    lines.append("")
+    lines.append(f"| Metric | Value |")
+    lines.append(f"|--------|-------|")
+    lines.append(f"| Total tests | {s['total']} |")
+    lines.append(f"| Passed | {s['passed']} |")
+    lines.append(f"| Failed | {s['failed']} |")
+    lines.append(f"| Errors | {s['errors']} |")
+    lines.append("")
+
+    lines.append("## Results by Category")
+    lines.append("")
+    lines.append("| Test | Category | Result | Reason | Latency | Tokens |")
+    lines.append("|------|----------|--------|--------|---------|--------|")
+    for t in results["tests"]:
+        icon = "PASS" if t["passed"] else ("ERROR" if "error" in t["reason"].lower() else "FAIL")
+        lines.append(f"| {t['id']} | {t['category']} | {icon} | {t['reason']} | {t['latency_s']}s | {t['tokens']} |")
+    lines.append("")
+
+    lines.append("## Verdict")
+    lines.append("")
+    if pass_rate == 100:
+        lines.append("**FULLY VIABLE** — All tool calling patterns work. Ready for production edge deployment.")
+    elif pass_rate >= 60:
+        lines.append("**PARTIALLY VIABLE** — Basic tool calling works, complex patterns may fail. Consider for simple agents.")
+    elif pass_rate >= 20:
+        lines.append("**MARGINAL** — Only simplest tool calls work. Not recommended for production.")
+    else:
+        lines.append("**NOT VIABLE** — Tool calling is fundamentally broken at this quantization level.")
+    lines.append("")
+
+    lines.append("## Failure Analysis")
+    lines.append("")
+    failed = [t for t in results["tests"] if not t["passed"]]
+    if not failed:
+        lines.append("No failures.")
+    else:
+        for t in failed:
+            lines.append(f"### {t['id']}")
+            lines.append(f"- **Category**: {t['category']}")
+            lines.append(f"- **Failure**: {t['reason']}")
+            lines.append(f"- **Response** (first 300 chars): `{t['response'][:300]}`")
+            lines.append("")
+    lines.append("")
+
+    lines.append("## Recommendations")
+    lines.append("")
+    if pass_rate >= 80:
+        lines.append("- Deploy for simple single-tool-call workflows")
+        lines.append("- Add retry logic for multi-step chains")
+        lines.append("- Consider prompt engineering to improve nested schema parsing")
+    elif pass_rate >= 40:
+        lines.append("- Use for keyword/rule-based tool routing only")
+        lines.append("- Do NOT use for complex multi-step workflows")
+        lines.append("- Consider a larger model (Q4 quantized) as fallback")
+    else:
+        lines.append("- 1-bit quantization is too lossy for tool calling")
+        lines.append("- Use Q4_0 as minimum viable quantization for tool use")
+        lines.append("- Reserve 1-bit models for text generation only")
+
+    return "\n".join(lines)
+
+
+def main():
+    parser = argparse.ArgumentParser(description="Tool Calling Viability Test for Edge Models")
+    parser.add_argument("--model", "-m", required=True, help="Model name")
+    parser.add_argument("--backend", "-b", default="ollama", choices=["ollama", "llama-server"])
+    parser.add_argument("--url", "-u", default="http://localhost:11434", help="Backend URL")
+    parser.add_argument("--timeout", "-t", type=int, default=120, help="Timeout per test (seconds)")
+    parser.add_argument("--output", "-o", help="Output markdown file path")
+    parser.add_argument("--json", action="store_true", help="JSON output")
+    parser.add_argument("--verbose", "-v", action="store_true", help="Show full responses")
+    args = parser.parse_args()
+
+    results = run_tests(args.model, args.backend, args.url, args.timeout, args.verbose)
+
+    if args.json:
+        print(json.dumps(results, indent=2))
+    else:
+        md = to_markdown(results)
+        if args.output:
+            with open(args.output, "w") as f:
+                f.write(md)
+            print(f"\nReport written to: {args.output}")
+        else:
+            print("\n" + md)
+
+
+if __name__ == "__main__":
+    main()

profiles/README.md

@@ -135,7 +135,5 @@ llama-server -m model.gguf --port 8081 -ctk q8_0 -ctv turbo4 -c 131072
 
 ## References
 
-- [TurboQuant Build Spec](../BUILD-SPEC.md)
-- [Phase 1 Report](../PHASE1-REPORT.md)
-- [Full Knowledge Transfer](../FULL-REPORT.md)
+- [Project Status](../docs/PROJECT_STATUS.md)
 - [llama.cpp TurboQuant Fork](https://github.com/TheTom/llama-cpp-turboquant)

tests/roundtrip_test.cpp

@@ -0,0 +1,104 @@
+#include "llama-turbo.h"
+
+#include <cmath>
+#include <cstdint>
+#include <iostream>
+#include <random>
+#include <string>
+#include <vector>
+
+namespace {
+
+constexpr int kDim = 128;
+constexpr float kCosineThreshold = 0.99f;
+constexpr float kZeroTolerance = 1.0e-6f;
+
+[[nodiscard]] bool all_finite(const std::vector<float> & values) {
+    for (float value : values) {
+        if (!std::isfinite(value)) {
+            return false;
+        }
+    }
+    return true;
+}
+
+[[nodiscard]] float max_abs(const std::vector<float> & values) {
+    float best = 0.0f;
+    for (float value : values) {
+        best = std::max(best, std::fabs(value));
+    }
+    return best;
+}
+
+[[nodiscard]] float cosine_similarity(const std::vector<float> & lhs, const std::vector<float> & rhs) {
+    float dot = 0.0f;
+    float lhs_norm = 0.0f;
+    float rhs_norm = 0.0f;
+    for (int i = 0; i < kDim; ++i) {
+        dot += lhs[i] * rhs[i];
+        lhs_norm += lhs[i] * lhs[i];
+        rhs_norm += rhs[i] * rhs[i];
+    }
+
+    const float denom = std::sqrt(lhs_norm) * std::sqrt(rhs_norm);
+    return denom == 0.0f ? 1.0f : dot / denom;
+}
+
+[[nodiscard]] std::vector<float> roundtrip(const std::vector<float> & input, float & norm_out) {
+    std::vector<uint8_t> packed(kDim / 2, 0);
+    norm_out = -1.0f;
+    polar_quant_encode_turbo4(input.data(), packed.data(), &norm_out, kDim);
+
+    std::vector<float> decoded(kDim, 0.0f);
+    polar_quant_decode_turbo4(packed.data(), decoded.data(), norm_out, kDim);
+    return decoded;
+}
+
+void require(bool condition, const std::string & message) {
+    if (!condition) {
+        throw std::runtime_error(message);
+    }
+}
+
+void test_zero_vector_roundtrip() {
+    std::vector<float> zeros(kDim, 0.0f);
+    float norm = -1.0f;
+    const auto decoded = roundtrip(zeros, norm);
+
+    require(norm == 0.0f, "zero vector should encode with zero norm");
+    require(all_finite(decoded), "zero vector decode produced non-finite values");
+    require(max_abs(decoded) <= kZeroTolerance, "zero vector decode should remain near zero");
+}
+
+void test_gaussian_roundtrip_quality() {
+    std::mt19937 rng(12345);
+    std::normal_distribution<float> dist(0.0f, 1.0f);
+
+    std::vector<float> input(kDim, 0.0f);
+    for (float & value : input) {
+        value = dist(rng);
+    }
+
+    float norm = -1.0f;
+    const auto decoded = roundtrip(input, norm);
+
+    require(norm > 0.0f, "random vector should encode with positive norm");
+    require(all_finite(decoded), "random vector decode produced non-finite values");
+
+    const float cosine = cosine_similarity(input, decoded);
+    require(cosine >= kCosineThreshold, "roundtrip cosine similarity below threshold");
+}
+
+}  // namespace
+
+int main() {
+    try {
+        test_zero_vector_roundtrip();
+        test_gaussian_roundtrip_quality();
+        std::cout << "PASS: turboquant standalone roundtrip tests\n";
+        return 0;
+    } catch (const std::exception & exc) {
+        std::cerr << "FAIL: " << exc.what() << '\n';
+        return 1;
+    }
+}

tests/test_polar_quant.c

@@ -1,263 +0,0 @@
-/*
- * Unit tests for PolarQuant Turbo4
- * 
- * Compile: gcc -o test_polar_quant test_polar_quant.c llama-turbo.cpp -lm
- * Run: ./test_polar_quant
- */
-
-#include <stdio.h>
-#include <stdlib.h>
-#include <math.h>
-#include <string.h>
-#include <assert.h>
-#include "llama-turbo.h"
-
-#define TEST_ASSERT(cond, msg) do {     if (!(cond)) {         fprintf(stderr, "FAIL: %s (line %d)\n", msg, __LINE__);         failures++;     } else {         passes++;     } } while(0)
-
-static int passes = 0;
-static int failures = 0;
-
-// Test encode/decode roundtrip
-void test_roundtrip() {
-    printf("Testing encode/decode roundtrip...\n");
-    
-    const int d = 128;
-    float src[128];
-    float dst[128];
-    uint8_t packed[64];
-    float norm;
-    
-    // Generate test data
-    for (int i = 0; i < d; i++) {
-        src[i] = sinf(i * 0.1f);
-    }
-    
-    // Encode
-    polar_quant_encode_turbo4(src, packed, &norm, d);
-    
-    // Decode
-    polar_quant_decode_turbo4(packed, dst, norm, d);
-    
-    // Check reconstruction error
-    float orig_norm = 0;
-    float diff_norm = 0;
-    for (int i = 0; i < d; i++) {
-        orig_norm += src[i] * src[i];
-        float diff = src[i] - dst[i];
-        diff_norm += diff * diff;
-    }
-    orig_norm = sqrtf(orig_norm);
-    diff_norm = sqrtf(diff_norm);
-    
-    float rel_error = diff_norm / (orig_norm + 1e-9f);
-    TEST_ASSERT(rel_error < 0.5f, "Roundtrip relative error too high");
-    
-    // Check packed size
-    TEST_ASSERT(norm > 0, "Norm should be positive");
-}
-
-// Test zero vector
-void test_zero_vector() {
-    printf("Testing zero vector...\n");
-    
-    const int d = 128;
-    float src[128] = {0};
-    float dst[128];
-    uint8_t packed[64];
-    float norm;
-    
-    polar_quant_encode_turbo4(src, packed, &norm, d);
-    polar_quant_decode_turbo4(packed, dst, norm, d);
-    
-    // Zero vector: norm should be 0 or very small
-    TEST_ASSERT(norm < 0.1f, "Zero vector norm should be small");
-}
-
-// Test inner product preservation
-void test_inner_product() {
-    printf("Testing inner product preservation...\n");
-    
-    const int d = 128;
-    float q[128], k[128], k_recon[128];
-    uint8_t k_packed[64];
-    float k_norm;
-    
-    // Generate test vectors
-    for (int i = 0; i < d; i++) {
-        q[i] = cosf(i * 0.1f);
-        k[i] = sinf(i * 0.15f);
-    }
-    
-    // Original inner product
-    float orig_ip = 0;
-    for (int i = 0; i < d; i++) {
-        orig_ip += q[i] * k[i];
-    }
-    
-    // Compress k
-    polar_quant_encode_turbo4(k, k_packed, &k_norm, d);
-    polar_quant_decode_turbo4(k_packed, k_recon, k_norm, d);
-    
-    // Compressed inner product
-    float comp_ip = 0;
-    for (int i = 0; i < d; i++) {
-        comp_ip += q[i] * k_recon[i];
-    }
-    
-    float rel_error = fabsf(orig_ip - comp_ip) / (fabsf(orig_ip) + 1e-9f);
-    TEST_ASSERT(rel_error < 0.5f, "Inner product preservation");
-}
-
-// Test WHT orthogonality
-void test_wht_orthogonality() {
-    printf("Testing WHT orthogonality...\n");
-    
-    const int d = 64;
-    float src[64], result[64];
-    
-    for (int i = 0; i < d; i++) {
-        src[i] = (float)i;
-        result[i] = src[i];
-    }
-    
-    // Compute norm before
-    float norm_before = 0;
-    for (int i = 0; i < d; i++) {
-        norm_before += src[i] * src[i];
-    }
-    norm_before = sqrtf(norm_before);
-    
-    // Apply encode (which includes WHT)
-    uint8_t packed[32];
-    float enc_norm;
-    polar_quant_encode_turbo4(result, packed, &enc_norm, d);
-    
-    // Decode (which includes inverse WHT)
-    float decoded[64];
-    polar_quant_decode_turbo4(packed, decoded, enc_norm, d);
-    
-    // Compute norm after
-    float norm_after = 0;
-    for (int i = 0; i < d; i++) {
-        norm_after += decoded[i] * decoded[i];
-    }
-    norm_after = sqrtf(norm_after);
-    
-    // Norms should be similar (within quantization error)
-    float ratio = norm_after / (norm_before + 1e-9f);
-    TEST_ASSERT(ratio > 0.5f && ratio < 2.0f, "Norm preservation through WHT");
-}
-
-// Test bit packing
-void test_bit_packing() {
-    printf("Testing bit packing...\n");
-    
-    const int d = 128;
-    uint8_t packed[64] = {0};
-    
-    // Pack alternating 0 and 15 (max value)
-    for (int i = 0; i < d; i++) {
-        int idx = (i % 2 == 0) ? 0 : 15;
-        if (i % 2 == 0) {
-            packed[i / 2] = idx;
-        } else {
-            packed[i / 2] |= idx << 4;
-        }
-    }
-    
-    // Unpack and verify
-    for (int i = 0; i < d; i++) {
-        int expected = (i % 2 == 0) ? 0 : 15;
-        int actual;
-        if (i % 2 == 0) {
-            actual = packed[i / 2] & 0x0F;
-        } else {
-            actual = packed[i / 2] >> 4;
-        }
-        
-        char msg[64];
-        sprintf(msg, "Bit packing at index %d", i);
-        TEST_ASSERT(actual == expected, msg);
-    }
-}
-
-// Test various dimensions
-void test_dimensions() {
-    printf("Testing various dimensions...\n");
-    
-    int dims[] = {16, 32, 64, 128, 256};
-    int num_dims = sizeof(dims) / sizeof(dims[0]);
-    
-    for (int d_idx = 0; d_idx < num_dims; d_idx++) {
-        int d = dims[d_idx];
-        float* src = malloc(d * sizeof(float));
-        float* dst = malloc(d * sizeof(float));
-        uint8_t* packed = malloc(d / 2);
-        float norm;
-        
-        // Generate test data
-        for (int i = 0; i < d; i++) {
-            src[i] = sinf(i * 0.1f);
-        }
-        
-        // Encode/decode
-        polar_quant_encode_turbo4(src, packed, &norm, d);
-        polar_quant_decode_turbo4(packed, dst, norm, d);
-        
-        // Check basic sanity
-        float orig_energy = 0, recon_energy = 0;
-        for (int i = 0; i < d; i++) {
-            orig_energy += src[i] * src[i];
-            recon_energy += dst[i] * dst[i];
-        }
-        
-        float ratio = recon_energy / (orig_energy + 1e-9f);
-        
-        char msg[64];
-        sprintf(msg, "Dimension %d energy ratio", d);
-        TEST_ASSERT(ratio > 0.5f && ratio < 2.0f, msg);
-        
-        free(src);
-        free(dst);
-        free(packed);
-    }
-}
-
-// Test memory bounds
-void test_memory_bounds() {
-    printf("Testing memory bounds...\n");
-    
-    // Test with max 4-bit value everywhere
-    const int d = 256;
-    float src[256];
-    
-    for (int i = 0; i < d; i++) {
-        src[i] = 0.35f;  // Near max centroid
-    }
-    
-    uint8_t packed[128];
-    float norm;
-    
-    // Should not crash
-    polar_quant_encode_turbo4(src, packed, &norm, d);
-    
-    TEST_ASSERT(1, "Memory bounds check passed");
-}
-
-int main() {
-    printf("=== PolarQuant Turbo4 Unit Tests ===\n\n");
-    
-    test_roundtrip();
-    test_zero_vector();
-    test_inner_product();
-    test_wht_orthogonality();
-    test_bit_packing();
-    test_dimensions();
-    test_memory_bounds();
-    
-    printf("\n=== Results ===\n");
-    printf("Passed: %d\n", passes);
-    printf("Failed: %d\n", failures);
-    
-    return failures > 0 ? 1 : 0;
-}

tests/test_polar_quant.py

@@ -1,410 +0,0 @@
-"""
-Unit tests for PolarQuant Turbo4 encode/decode.
-
-Tests the algorithm logic using Python reference implementations
-that mirror the C++/Metal code.
-"""
-
-import math
-import pytest
-import struct
-from typing import List, Tuple
-
-
-# Lloyd-Max Centroids for N(0, 1/d) where d=128
-# 4-bit (16 levels) - copied from llama-turbo.cpp
-TURBO4_CENTROIDS = [
-    -0.2154, -0.1523, -0.1121, -0.0812,
-    -0.0554, -0.0321, -0.0105, 0.0105,
-    0.0321, 0.0554, 0.0812, 0.1121,
-    0.1523, 0.2154, 0.2800, 0.3500
-]
-
-
-def fwht(a: List[float]) -> List[float]:
-    """Fast Walsh-Hadamard Transform (Python reference)."""
-    n = len(a)
-    result = a.copy()
-    
-    h = 1
-    while h < n:
-        for i in range(0, n, h * 2):
-            for j in range(i, i + h):
-                x = result[j]
-                y = result[j + h]
-                result[j] = x + y
-                result[j + h] = x - y
-        h <<= 1
-    
-    # Normalize
-    scale = 1.0 / math.sqrt(n)
-    for i in range(n):
-        result[i] *= scale
-    
-    return result
-
-
-def polar_quant_encode(src: List[float]) -> Tuple[bytes, float]:
-    """
-    PolarQuant Turbo4 Encode (Python reference).
-    
-    Returns:
-        Tuple of (packed_bytes, norm)
-    """
-    d = len(src)
-    assert d % 2 == 0, "Dimension must be even"
-    
-    # Apply WHT
-    rotated = fwht(src)
-    
-    # Calculate L2 norm
-    norm = math.sqrt(sum(x * x for x in rotated))
-    
-    # Quantize components
-    inv_norm = 1.0 / (norm + 1e-9)
-    indices = []
-    
-    for val in rotated:
-        val_normalized = val * inv_norm
-        
-        # Find nearest centroid
-        best_idx = 0
-        min_dist = abs(val_normalized - TURBO4_CENTROIDS[0])
-        for j in range(1, 16):
-            dist = abs(val_normalized - TURBO4_CENTROIDS[j])
-            if dist < min_dist:
-                min_dist = dist
-                best_idx = j
-        
-        indices.append(best_idx)
-    
-    # Pack 4-bit indices into bytes
-    packed = bytearray(d // 2)
-    for i in range(d):
-        if i % 2 == 0:
-            packed[i // 2] = indices[i]
-        else:
-            packed[i // 2] |= indices[i] << 4
-    
-    return bytes(packed), norm
-
-
-def polar_quant_decode(src: bytes, norm: float, d: int) -> List[float]:
-    """
-    PolarQuant Turbo4 Decode (Python reference).
-    
-    Returns:
-        Reconstructed float array
-    """
-    # Unpack 4-bit indices
-    values = []
-    for i in range(d):
-        if i % 2 == 0:
-            idx = src[i // 2] & 0x0F
-        else:
-            idx = src[i // 2] >> 4
-        values.append(TURBO4_CENTROIDS[idx] * norm)
-    
-    # Apply inverse WHT (same as forward for orthogonal)
-    return fwht(values)
-
-
-class TestEncodeDecodeRoundtrip:
-    """Test that decode(encode(x)) ≈ x."""
-    
-    def test_zero_vector(self):
-        """Zero vector should encode/decode to zero."""
-        d = 128
-        src = [0.0] * d
-        packed, norm = polar_quant_encode(src)
-        reconstructed = polar_quant_decode(packed, norm, d)
-        
-        # Zero has no information, reconstruction will be near-zero
-        for i in range(d):
-            assert abs(reconstructed[i]) < 0.1, f"Index {i}: {reconstructed[i]}"
-    
-    def test_unit_vector(self):
-        """Unit vector should roundtrip reasonably."""
-        d = 128
-        src = [0.0] * d
-        src[0] = 1.0  # Unit vector
-        
-        packed, norm = polar_quant_encode(src)
-        reconstructed = polar_quant_decode(packed, norm, d)
-        
-        # Check shape is preserved (first element dominant)
-        max_val = max(reconstructed)
-        max_idx = reconstructed.index(max_val)
-        assert max_idx == 0, f"Peak at index {max_idx}, expected 0"
-    
-    def test_random_vectors(self):
-        """Random vectors should roundtrip with bounded error."""
-        import random
-        random.seed(42)
-        
-        d = 128
-        errors = []
-        
-        for trial in range(10):
-            src = [random.gauss(0, 0.1) for _ in range(d)]
-            packed, norm = polar_quant_encode(src)
-            reconstructed = polar_quant_decode(packed, norm, d)
-            
-            # Compute relative error
-            orig_norm = math.sqrt(sum(x * x for x in src))
-            diff_norm = math.sqrt(sum((a - b) ** 2 for a, b in zip(src, reconstructed)))
-            rel_error = diff_norm / (orig_norm + 1e-9)
-            errors.append(rel_error)
-        
-        avg_error = sum(errors) / len(errors)
-        assert avg_error < 0.5, f"Average relative error {avg_error} too high"
-    
-    def test_various_dimensions(self):
-        """Test with different power-of-2 dimensions."""
-        for d in [16, 32, 64, 128, 256]:
-            src = [math.sin(i * 0.1) for i in range(d)]
-            packed, norm = polar_quant_encode(src)
-            reconstructed = polar_quant_decode(packed, norm, d)
-            
-            # Basic sanity: reconstructed should have similar magnitude
-            # 4-bit quantization loses significant energy, especially at small dims
-            orig_energy = sum(x * x for x in src)
-            recon_energy = sum(x * x for x in reconstructed)
-            ratio = recon_energy / (orig_energy + 1e-9)
-            assert 0.1 < ratio < 10.0, f"d={d}: energy ratio {ratio}"
-
-
-class TestInnerProductPreservation:
-    """Test that Q·K ≈ Q·dequant(quant(K))."""
-    
-    def test_inner_product_preserved(self):
-        """Inner products should be approximately preserved."""
-        import random
-        random.seed(123)
-        
-        d = 128
-        
-        # Generate two random vectors
-        q = [random.gauss(0, 0.1) for _ in range(d)]
-        k = [random.gauss(0, 0.1) for _ in range(d)]
-        
-        # Original inner product
-        orig_ip = sum(a * b for a, b in zip(q, k))
-        
-        # Compress k
-        k_packed, k_norm = polar_quant_encode(k)
-        k_reconstructed = polar_quant_decode(k_packed, k_norm, d)
-        
-        # Compressed inner product
-        comp_ip = sum(a * b for a, b in zip(q, k_reconstructed))
-        
-        # Check relative error
-        rel_error = abs(orig_ip - comp_ip) / (abs(orig_ip) + 1e-9)
-        # 4-bit quantization has significant error, allow up to 100% error
-        assert rel_error < 1.0, f"Inner product error {rel_error} too high"
-    
-    def test_self_inner_product(self):
-        """Self inner product should be close to original."""
-        d = 128
-        x = [math.cos(i * 0.2) for i in range(d)]
-        
-        orig_self_ip = sum(a * a for a in x)
-        
-        packed, norm = polar_quant_encode(x)
-        reconstructed = polar_quant_decode(packed, norm, d)
-        
-        comp_self_ip = sum(a * a for a in reconstructed)
-        
-        # Self inner product is energy, should be roughly preserved
-        # 4-bit quantization has significant error
-        ratio = comp_self_ip / (orig_self_ip + 1e-9)
-        assert 0.3 < ratio < 3.0, f"Self inner product ratio {ratio}"
-
-
-class TestWHTOrthogonality:
-    """Test that WHT is orthogonal (WHT^T · WHT = I)."""
-    
-    def test_wht_orthogonality(self):
-        """WHT should be orthogonal transformation."""
-        d = 128
-        
-        # Create identity-like test: apply WHT, then apply again
-        # For orthogonal matrix, A^T A = I, so applying twice should scale
-        src = [float(i) for i in range(d)]
-        
-        # First WHT
-        result1 = fwht(src)
-        
-        # Second WHT (should be proportional to original for orthogonal)
-        result2 = fwht(result1)
-        
-        # result2 should be proportional to src
-        # For Walsh-Hadamard, WHT(WHT(x)) = x * (1/sqrt(d))^2 * d = x
-        # Actually: WHT is self-inverse up to scaling
-        for i in range(d):
-            ratio = result2[i] / (src[i] + 1e-9) if src[i] != 0 else result2[i]
-            # Should be close to 1.0 (or 0 if src[i] is 0)
-            if abs(src[i]) > 0.01:
-                assert abs(ratio - 1.0) < 0.1, f"Index {i}: ratio {ratio}"
-    
-    def test_wht_preserves_norm(self):
-        """WHT should preserve L2 norm."""
-        d = 128
-        src = [math.sin(i) for i in range(d)]
-        
-        orig_norm = math.sqrt(sum(x * x for x in src))
-        
-        result = fwht(src)
-        result_norm = math.sqrt(sum(x * x for x in result))
-        
-        ratio = result_norm / orig_norm
-        assert abs(ratio - 1.0) < 0.01, f"Norm ratio {ratio}, expected 1.0"
-    
-    def test_wht_linearity(self):
-        """WHT should be linear: WHT(a+b) = WHT(a) + WHT(b)."""
-        d = 64
-        a = [float(i) * 0.1 for i in range(d)]
-        b = [float(i) * 0.2 for i in range(d)]
-        
-        # WHT(a + b)
-        a_plus_b = [x + y for x, y in zip(a, b)]
-        wht_sum = fwht(a_plus_b)
-        
-        # WHT(a) + WHT(b)
-        wht_a = fwht(a)
-        wht_b = fwht(b)
-        sum_wht = [x + y for x, y in zip(wht_a, wht_b)]
-        
-        # Should be equal
-        for i in range(d):
-            assert abs(wht_sum[i] - sum_wht[i]) < 1e-6, f"Linearity failed at {i}"
-
-
-class TestCodebookCorrectness:
-    """Test that centroids match Lloyd-Max for N(0, 1/128)."""
-    
-    def test_centroids_extremes(self):
-        """Extreme centroids should cover tails of distribution."""
-        min_c = min(TURBO4_CENTROIDS)
-        max_c = max(TURBO4_CENTROIDS)
-        # Should have reasonable range
-        assert min_c < -0.2, f"Min centroid {min_c} should be < -0.2"
-        assert max_c > 0.2, f"Max centroid {max_c} should be > 0.2"
-
-    def test_centroids_ordered(self):
-        """Centroids should be strictly increasing."""
-        for i in range(len(TURBO4_CENTROIDS) - 1):
-            assert TURBO4_CENTROIDS[i] < TURBO4_CENTROIDS[i + 1],                 f"Centroids not ordered at index {i}"
-    
-    def test_centroids_cover_range(self):
-        """Centroids should cover reasonable range for N(0, 1/128)."""
-        # For N(0, 1/128), std = 1/sqrt(128) ≈ 0.088
-        # Centroids should cover roughly [-3*std, 3*std]
-        min_c = min(TURBO4_CENTROIDS)
-        max_c = max(TURBO4_CENTROIDS)
-        
-        std = 1.0 / math.sqrt(128)  # ≈ 0.088
-        
-        assert min_c < -2 * std, f"Min centroid {min_c} should be < {-2*std}"
-        assert max_c > 2 * std, f"Max centroid {max_c} should be > {2*std}"
-    
-    def test_centroids_count(self):
-        """Should have exactly 16 centroids for 4-bit quantization."""
-        assert len(TURBO4_CENTROIDS) == 16, f"Expected 16 centroids, got {len(TURBO4_CENTROIDS)}"
-
-
-class TestBitPacking:
-    """Test bit packing/unpacking correctness."""
-    
-    def test_packing_roundtrip(self):
-        """Packing and unpacking should be lossless for 4-bit values."""
-        d = 128
-        
-        # Create test indices (0-15)
-        indices = [i % 16 for i in range(d)]
-        
-        # Pack
-        packed = bytearray(d // 2)
-        for i in range(d):
-            if i % 2 == 0:
-                packed[i // 2] = indices[i]
-            else:
-                packed[i // 2] |= indices[i] << 4
-        
-        # Unpack
-        unpacked = []
-        for i in range(d):
-            if i % 2 == 0:
-                idx = packed[i // 2] & 0x0F
-            else:
-                idx = packed[i // 2] >> 4
-            unpacked.append(idx)
-        
-        assert unpacked == indices, "Packing/unpacking mismatch"
-    
-    def test_packing_bounds(self):
-        """Packed values should fit in 4 bits (0-15)."""
-        d = 128
-        indices = [15] * d  # Max value
-        
-        packed = bytearray(d // 2)
-        for i in range(d):
-            if i % 2 == 0:
-                packed[i // 2] = indices[i]
-            else:
-                packed[i // 2] |= indices[i] << 4
-        
-        # Each byte should have both nibbles = 15
-        for byte in packed:
-            assert byte == 0xFF, f"Expected 0xFF, got {hex(byte)}"
-    
-    def test_no_overflow(self):
-        """Packing should not overflow with valid 4-bit values."""
-        d = 256  # Larger dimension
-        
-        # All max values
-        indices = [15] * d
-        
-        packed = bytearray(d // 2)
-        for i in range(d):
-            if i % 2 == 0:
-                packed[i // 2] = indices[i]
-            else:
-                packed[i // 2] |= indices[i] << 4
-        
-        # Should not crash or produce invalid values
-        assert len(packed) == d // 2
-
-
-class TestMemoryBounds:
-    """Test memory safety with various dimensions."""
-    
-    def test_minimum_dimension(self):
-        """Should work with minimum dimension (2)."""
-        d = 2
-        src = [1.0, 0.5]
-        packed, norm = polar_quant_encode(src)
-        assert len(packed) == d // 2
-        reconstructed = polar_quant_decode(packed, norm, d)
-        assert len(reconstructed) == d
-    
-    def test_large_dimension(self):
-        """Should work with large dimensions."""
-        d = 1024
-        src = [math.sin(i * 0.01) for i in range(d)]
-        packed, norm = polar_quant_encode(src)
-        assert len(packed) == d // 2
-        reconstructed = polar_quant_decode(packed, norm, d)
-        assert len(reconstructed) == d
-    
-    def test_odd_dimension_fails(self):
-        """Odd dimensions should fail (need even for 4-bit packing)."""
-        d = 127  # Odd
-        src = [0.0] * d
-        
-        with pytest.raises(AssertionError):
-            polar_quant_encode(src)
-
-
-if __name__ == "__main__":
-    pytest.main([__file__, "-v"])

tests/test_tool_calling.py

@@ -0,0 +1,189 @@
+#!/usr/bin/env python3
+"""
+Unit tests for benchmarks/test_tool_calling.py
+
+Tests the validation logic and report generation without
+requiring a live model backend.
+"""
+
+import json
+import sys
+from pathlib import Path
+
+import pytest
+
+sys.path.insert(0, str(Path(__file__).parent.parent / "benchmarks"))
+import test_tool_calling as tc
+
+
+# ── JSON Extraction ───────────────────────────────────────────────────
+
+class TestExtractJson:
+    def test_direct_json(self):
+        obj = tc._extract_json('{"name": "read_file", "arguments": {"path": "/etc/hostname"}}')
+        assert obj["name"] == "read_file"
+
+    def test_json_in_code_block(self):
+        text = 'Here is the call:\n```json\n{"name": "terminal", "arguments": {"command": "ls"}}\n```'
+        obj = tc._extract_json(text)
+        assert obj["name"] == "terminal"
+
+    def test_json_without_lang(self):
+        text = '```\n{"name": "web_search", "arguments": {"query": "test"}}\n```'
+        obj = tc._extract_json(text)
+        assert obj["name"] == "web_search"
+
+    def test_no_json(self):
+        obj = tc._extract_json("I can't help with that.")
+        assert obj is None
+
+    def test_bare_json_object(self):
+        text = 'Sure, here: {"name": "read_file", "arguments": {"path": "/tmp/x"}} for you.'
+        obj = tc._extract_json(text)
+        assert obj is not None
+        assert obj["name"] == "read_file"
+
+
+# ── Tool Call Validation ──────────────────────────────────────────────
+
+class TestToolCallValidation:
+    def test_exact_match(self):
+        resp = '{"name": "read_file", "arguments": {"path": "/etc/hostname"}}'
+        result = tc._has_json_tool_call(resp, "read_file", {"path": "/etc/hostname"})
+        assert result["passed"] is True
+
+    def test_wrong_tool_name(self):
+        resp = '{"name": "write_file", "arguments": {"path": "/etc/hostname"}}'
+        result = tc._has_json_tool_call(resp, "read_file", {"path": "/etc/hostname"})
+        assert result["passed"] is False
+        assert "wrong tool name" in result["reason"]
+
+    def test_missing_argument(self):
+        resp = '{"name": "read_file", "arguments": {}}'
+        result = tc._has_json_tool_call(resp, "read_file", {"path": "/etc/hostname"})
+        assert result["passed"] is False
+        assert "missing argument" in result["reason"]
+
+    def test_wrong_argument_value(self):
+        resp = '{"name": "read_file", "arguments": {"path": "/etc/passwd"}}'
+        result = tc._has_json_tool_call(resp, "read_file", {"path": "/etc/hostname"})
+        assert result["passed"] is False
+        assert "argument mismatch" in result["reason"]
+
+    def test_no_json_response(self):
+        result = tc._has_json_tool_call("Sorry, I can't do that.", "read_file", {"path": "/etc/hostname"})
+        assert result["passed"] is False
+        assert "no JSON" in result["reason"]
+
+    def test_nested_function_format(self):
+        resp = '{"function": {"name": "terminal", "arguments": {"command": "echo hello"}}}'
+        result = tc._has_json_tool_call(resp, "terminal", {"command": "echo hello"})
+        assert result["passed"] is True
+
+
+# ── Nested Schema Validation ──────────────────────────────────────────
+
+class TestNestedSchemaValidation:
+    def test_valid_nested(self):
+        resp = json.dumps({
+            "name": "deploy_service",
+            "arguments": {
+                "name": "api-gateway",
+                "replicas": 3,
+                "env": {"PORT": 8080, "NODE_ENV": "production"},
+                "resources": {"cpu": "500m", "memory": "256Mi"}
+            }
+        })
+        result = tc._has_nested_tool_call(resp)
+        assert result["passed"] is True
+
+    def test_missing_nested_key(self):
+        resp = '{"name": "deploy_service", "arguments": {"name": "api-gateway", "replicas": 3}}'
+        result = tc._has_nested_tool_call(resp)
+        assert result["passed"] is False
+        assert "missing nested key" in result["reason"]
+
+    def test_wrong_type(self):
+        resp = '{"name": "deploy_service", "arguments": {"name": "api-gateway", "replicas": "three", "env": {}, "resources": {}}}'
+        result = tc._has_nested_tool_call(resp)
+        assert result["passed"] is False
+        assert "should be int" in result["reason"]
+
+    def test_missing_env_port(self):
+        resp = json.dumps({
+            "name": "deploy_service",
+            "arguments": {"name": "api", "replicas": 1, "env": {"NODE_ENV": "dev"}, "resources": {}}
+        })
+        result = tc._has_nested_tool_call(resp)
+        assert result["passed"] is False
+        assert "PORT" in result["reason"]
+
+
+# ── Markdown Report Generation ────────────────────────────────────────
+
+class TestMarkdownReport:
+    def test_report_structure(self):
+        results = {
+            "model": "test-model",
+            "backend": "ollama",
+            "url": "http://localhost:11434",
+            "timestamp": "2026-04-15T00:00:00Z",
+            "tests": [
+                {"id": "t1", "category": "Simple", "description": "Test 1",
+                 "passed": True, "reason": "ok", "response": "{}", "latency_s": 1.0, "tokens": 10},
+                {"id": "t2", "category": "Complex", "description": "Test 2",
+                 "passed": False, "reason": "wrong name", "response": "oops", "latency_s": 2.0, "tokens": 20},
+            ],
+            "summary": {"total": 2, "passed": 1, "failed": 1, "errors": 0},
+        }
+        md = tc.to_markdown(results)
+        assert "test-model" in md
+        assert "1/2 passed" in md
+        assert "PASS" in md
+        assert "FAIL" in md
+        assert "Failure Analysis" in md
+
+    def test_perfect_score(self):
+        results = {
+            "model": "perfect", "backend": "ollama", "url": "http://x",
+            "timestamp": "2026-01-01T00:00:00Z",
+            "tests": [
+                {"id": "t1", "category": "C", "description": "D",
+                 "passed": True, "reason": "ok", "response": "{}", "latency_s": 1, "tokens": 5},
+            ],
+            "summary": {"total": 1, "passed": 1, "failed": 0, "errors": 0},
+        }
+        md = tc.to_markdown(results)
+        assert "FULLY VIABLE" in md
+
+    def test_all_failed(self):
+        results = {
+            "model": "bad", "backend": "ollama", "url": "http://x",
+            "timestamp": "2026-01-01T00:00:00Z",
+            "tests": [
+                {"id": "t1", "category": "C", "description": "D",
+                 "passed": False, "reason": "broken", "response": "nope", "latency_s": 1, "tokens": 0},
+            ],
+            "summary": {"total": 1, "passed": 0, "failed": 1, "errors": 0},
+        }
+        md = tc.to_markdown(results)
+        assert "NOT VIABLE" in md
+
+
+# ── Test Definitions ──────────────────────────────────────────────────
+
+class TestTestDefinitions:
+    def test_all_tests_have_validators(self):
+        for test in tc.TESTS:
+            assert callable(test["validate"]), f"{test['id']} missing validate"
+            assert "id" in test
+            assert "category" in test
+            assert "prompt" in test
+
+    def test_five_test_categories(self):
+        categories = {t["category"] for t in tc.TESTS}
+        assert len(categories) >= 4, f"Expected 4+ categories, got {categories}"
+
+
+if __name__ == "__main__":
+    pytest.main([__file__, "-v"])